水稻模拟模型在高温敏感性研究中的应用

doi:10.3724/SP.J.1258.2014.00048

摘要/Abstract

摘要：

以调试校正较高精度的ORYZA2000模型参数及高温敏感性模拟验证为目的, 为模型适应性和本地化提供依据, 利用江苏省9个试验点5个水稻(Oryza sativa)品种的田间观测数据及当地逐日气象数据, 采用ORYZA2000最新版本(V2.13)水稻生长模型, 首先挑选出5个试验点3个品种的观测数据进行模型参数适应性调试校正, 确定了水稻发育生长阶段的各项参数, 然后用该参数对独立样本的4个试验点2个水稻品种地上部分各器官生物量、叶面积指数动态变化过程及最终产量进行了动态模拟。通过t检验和质量评价指标对模拟结果进行了显著性检验。利用通过检验的模型及其参数在假设环境温度不同时间段的持续升高条件下, 开展了高温对水稻生物量及产量影响的模拟研究, 模拟结果的影响幅度与实际高温处理结果的影响幅度进行了比较。结果表明: 1)经过调试校正获得较高精度的水稻发育阶段各参数, 较准确地模拟了水稻生物量和叶面积指数的动态累积过程, 模拟值与观测值基本一致, 说明校正后参数的合理性和有效性; 2)调整参数后高温敏感性模拟结果表明, 孕穗期到开花期温度连续3天、5天、7天升高到35 ℃时, 总生物量、穗生物量和总产量与对照(CK)相比分别下降了12%-25%; 不同时间段连续升高到38 ℃时下降18%-31%; 不同时间段升高到41 ℃时, 各生物量与对照相比分别下降了20%-38%。模型模拟值与控制试验室的观测数据的下降幅度基本一致, 表明经过参数校正的ORYZA2000可以应用于水稻对气温升高响应的预测。

关键词: 生物量, 高温影响, 检验及评价, 水稻, 模拟

Abstract:

Aims For adoption and localization of the high precision rice growth model ORYZA2000, the model parameters were calibrated and high-temperature sensitivity analysis was performed based on observed data for five rice varieties at nine experimental stations and daily meteorological data in Jiangsu Province.
Methods The latest version of ORYZA2000 (V2.13) was used in this study. The model parameters were calibrated using the observed data for three rice varieties at five experimental stations, and then the aboveground biomass, leaf area index, and final yield were estimated for two other rice varieties at four experimental stations for model validation; a t-test was performed for quality evaluation. By using the validated model and raising the temperature at different time periods, a simulation of high temperature impact on rice biomass and yield was carried out. The simulation results were compared with the observational data from the greenhouse experiments assessing the high temperature responses of the rice varieties studied.
Important findings The results show that after calibration, the model parameters reliably simulated the dynamics of biomass accumulation and leaf area index development in the rice varieties studied; the simulated values are consistent with the observed values. The total biomass, panicle biomass, and final yield decreased by 12%-25% compared to the control (CK) when the growth temperature was raised to 35 °C for 3, 5 and 7 consecutive days from booting to flowering stages. Those values decreased by 18%-31% when the temperature was raised to 38 °C and by 20%-38% when the temperature was raised to 41 °C over the same periods. In general, the magnitudes of decline in the growth of rice varieties from model simulations were comparable with controlled laboratory observations. ORYZA2000 model could be applied to predict rice response to temperature increase on the basis of crop parameter calibrations.

Key words: biomass, high-temperature influence, inspection and evaluation, rice, simulation

沙依然·外力,李秉柏,张佳华,杨沈斌. 水稻模拟模型在高温敏感性研究中的应用. 植物生态学报, 2014, 38(5): 515-528. DOI: 10.3724/SP.J.1258.2014.00048

SAYRAN• Waley,LI Bing-Bai,ZHANG Jia-Hua,YANG Shen-Bin. Application of a rice simulation model in high temperature sensitivity study. Chinese Journal of Plant Ecology, 2014, 38(5): 515-528. DOI: 10.3724/SP.J.1258.2014.00048

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链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2014.00048

https://www.plant-ecology.com/CN/Y2014/V38/I5/515

图/表 13

表1 水稻品种、类型和栽培方式

Table 1 Varieties, types and cultivation methods of rice

试验点 Study location	地点 Location	经纬度 Longitude and latitude	栽培方式 Cultivation method	水稻品种 Rice variety	水稻类型 Rice type
SD1	邗江沙头 Shatou, Hanjiang	119.56° E, 32.28° N	机械栽插 Mechanical transplanting	‘扬粳4227’ ‘Yangjing 4227’	早熟粳稻 Early-maturing Japonica rice
SD2	江都七里 Qili, Jiangdu	119.69° E, 32.51° N	直接播种 Direct broadcasting	‘镇稻88’ ‘Zhendao 88’	中熟晚粳 Medium-maturing Japonica rice
SD3	江都樊川 Fanchuan, Jiangdu	119.68° E, 32.68° N	直接播种 Direct broadcasting	‘淮稻5号’ ‘Huaidao 5’	晚熟粳稻 Late-maturing Japonica rice
SD4	兴化临城 Lincheng, Xinghua	119.80° E, 32.84° N	直接播种 Direct broadcasting	‘淮稻5号’ ‘Huaidao 5’	晚熟粳稻 Late-maturing Japonica rice
SD5	兴化昌荣 Changrong, Xinghua	120.10° E, 32.94° N	直接播种 Direct broadcasting	‘淮稻5号’ ‘Huaidao 5’	晚熟粳稻 Late-maturing Japonica rice
SD6	宝应子婴 Ziying, Baoying	119.54° E, 33.04° N	直接播种 Direct broadcasting	‘淮稻5号’ ‘Huaidao 5’	晚熟粳稻 Late-maturing Japonica rice
SD7	金湖涂沟 Tugou, Jinhu	119.23° E, 33.06° N	人工栽植 Artificial transplanting	‘C两优608’ ‘C Liangyou 608’	杂交稻 Late-maturing Indica rice
SD8	金湖戴楼 Dailou, Jinhu	118.88° E, 33.02° N	人工栽植 Artificial transplanting	‘Y两优1’ ‘Y Liangyou 1’	杂交稻 Late-maturing Indica rice
SD9	洪泽马坝 Maba, Hongze	118.89° E, 33.25° N	机械栽插 Mechanical transplanting	‘淮稻5号’ ‘Huaidao 5’	晚熟粳稻 Late-maturing Japonica rice

表2 水稻物候期测定(月/日)

Table 2 Determination of rice phenological stages (month/day)

试验点 Study location	播种期 Sowing date	出苗日期 Emergence date	移栽期 Transplanting date	孕穗期 Booting date	抽穗期 Heading date	开花期 Flowering date	成熟期 Physiological maturity date
SD1 SD2 SD3 SD4 SD5 SD6 SD7 SD8 SD9	5/26 6/09 6/12 6/12 6/11 6/13 5/10 5/05 5/20	5/30 6/14 6/19 6/19 6/18 6/20 5/15 5/10 5/26	6/22 — — — — — 6/13 6/13 6/20	8/24 8/23 8/28 8/25 8/25 8/25 8/13 8/17 8/22	9/01 8/30 9/05 9/02 9/02 9/02 8/20 8/24 8/30	9/03 9/01 9/07 9/04 9/04 9/04 8/22 8/26 9/01	10/21 10/17 10/20 10/20 10/20 10/21 10/10 10/12 10/21

表3 由定标程序获取的试验点水稻发育速率参数

Table 3 Phenological development parameters derived from calibration with the rest used in modeling the phenological development of rice grown in the experimental field

试验点 Study location	水稻品种 Rice variety	发育速率参数 Development parameter
试验点 Study location	水稻品种 Rice variety	基本营养阶段 Juvenile phase (°C·d^-1)	光敏感阶段 Photoperiod-sensitive phase (°C·d^-1)	穗形成阶段 Panicle development phase (°C·d^-1)	籽粒灌浆阶段 Reproductive phase (°C·d^-1)
模型默认值 Default value of model		0.000 773	0.000 758	0.000 784	0.001 784
SD1	‘扬粳4227’ ‘Yangjing 4227’	0.000 449	0.000 758	0.000 795	0.001 621
SD2	‘镇稻88’ ‘Zhendao 88’	0.000 583	0.000 758	0.000 795	0.001 622
SD4	‘淮稻5号’ ‘Huaidao 5’	0.000 664	0.000 758	0.000 785	0.001 635
SD6	‘淮稻5号’ ‘Huaidao 5’	0.000 577	0.000 758	0.000 785	0.001 665
SD7	‘C两优608’ ‘C Liangyou 608’	0.000 506	0.000 758	0.000 795	0.001 570

图1 不同观测地点不同品种水稻生物量的模拟值与实测值。A, 邗江沙头。B, 江都七里。C, 兴化临城。D, 金湖涂沟。

Fig. 1 Simulations with calibrated model and observed biomass for different rice varieties at different study locations. A, Shatou, Hanjiang. B, Qili, Jiangdu. C, Lincheng, Xinghua. D, Tugou, Jinhu.

图2 模型定标校正后对不同观测区不同品种水稻叶面积指数的模拟值与实测值。A, 邗江沙头。B, 江都七里。C, 兴化临城。D, 金湖涂沟。

Fig. 2 Simulations with calibrated model and observed leaf area index for different rice varieties at different study locations. A, Shatou, Hanjiang. B, Qili, Jiangdu. C, Lincheng, Xinghua. D, Tugou, Jinhu.

图3 模型定标后的水稻各生物量的模拟值与实测值对应图。A, 江都樊川。B, 兴化昌荣。C, 金湖戴楼。D, 洪泽马坝。

Fig. 3 Simulations with calibrated model and observed biomass for different rice varieties at different study locations. A, Fanchuan, Jiangdu. B, Changrong, Xinghua. C, Dailou, Jinhu. D, Maba, Hongze.

图4 模型定标校正后的水稻叶面积指数的模拟值与实测值对应图。A, 江都樊川(SD3)。B, 兴化昌荣(SD5)。C, 金湖戴楼(SD8)。D, 洪泽马坝(SD9)。

Fig. 4 Simulations with calibrated model and observed leaf area index for different rice varieties at different study locations. A, Fanchuan, Jiangdu. B, Changrong, Xinghua. C, Dailou, Jinhu. D, Maba, Hongze.

图5 水稻生物量模拟值与实测值对比验证。

Fig. 5 Comparison between simulated and observed rice yield.

表4 各器官生物量模拟效果检验值

Table 4 Tests of simulated biomass for different organs

	地上部分总生物量 Total aboveground biomass				绿叶生物量 Green leaf biomass				茎生物量 Stem biomass				穗生物量 Panicle biomass
	t	R	AE	NR	t	R	AE	NR	t	R	AE	NR	t	R	AE	NR
SD3	2.55	0.977	14	23	-0.10	0.975	16	18	-1.51	0.979	18	22	1.57	0.972	17	45
SD5	1.91	0.966	17	13	-0.01	0.976	11	13	-0.03	0.971	17	12	1.58	0.971	15	46
SD8	0.44	0.951	15	19	-3.53	0.965	14	18	-1.15	0.965	13	19	0.53	0.922	34	20
SD9	-1.00	0.972	28	14	-0.19	0.985	15	10	2.37	0.974	28	13	-1.28	0.967	15	25

表5 叶面积指数模拟效果检验值

Table 5 Tests of simulated leaf area index

	叶面积指数 Leaf area index
	t	R	AE	NR
SD3	1.66	0.976	26	19
SD5	-0.30	0.962	17	12
SD8	0.90	0.956	20	33
SD9	-1.16	0.960	14	20

图6 不同观测区域不同品种水稻模拟产量值与理论产量值。试验点同表1。

Fig. 6 Simulated and observed rice yields for different rice varieties at different study locations. See Table 1 for description of study locations.

图7 高温对水稻各生物量及产量影响的模拟结果(平均值±标准误差)。A, ‘镇稻88’。B, ‘淮稻5’。CK, 对照; 1-9分别为3天35 ℃、5天35 ℃、7天35 ℃、3天38 ℃、5天38 ℃、7天38 ℃、3天41 ℃、5天41 ℃、7天41 ℃。

Fig. 7 Simulations of the influence of high temperature on rice biomass and yield (mean ± SE). A, ‘Zhendao 88’. B, ‘Huaidao 5’. CK, control; 1-9 is 35 °C for 3 days, 35 °C for 5 days, 35 °C for 7 days, 38 °C for 3 days, 38 °C for 5 days, 38 °C for 7 days, 41 °C for 3 days, 41 °C for 5 days, 41 °C for 7 days.

图8 控制实验室做的高温对水稻各生物量及产量影响的实测结果(平均值±标准误差)。A, ‘镇稻88’。B, ‘淮稻5’。CK, 对照; 1-6分别为3天35 ℃、5天35 ℃、3天38 ℃、5天38 ℃、3天41 ℃、5天41 ℃。

Fig. 8 Controlled laboratory measurements of the influence of high temperature on rice biomass and yield (mean ± SE). A, ‘Zhendao 88’. B, ‘Huaidao 5’. CK, control; 1-6 is 35 °C for 3 days, 35 °C for 5 days, 38 °C for 3 days, 38 °C for 5 days, 41 °C for 3 days, 41 °C for 5 days.

参考文献 20

[1]	Amiri E (2008). Evaluation of the rice growth model ORYZA2000 under water management. Asian Journal of Plant Sciences, 7, 291-297.
[2]	Bouman BAM, Kropff MJ, Tuong TP, Woppereis MCS, ten Berge HFM, van Laar HH (2001). ORYZA2000: Modeling Lowland Rice. IRRI, Wageningen. 235.
[3]	Duan H, Yang JC (2012). Research advances in the effect of high temperature on rice and its mechanism. Chinese Journal of Rice Science, 26, 393-400. (in Chinese with English abstract).
	[ 段骅, 杨建昌 (2012). 高温对水稻的影响及其机制的研究进展. 中国水稻科学, 26, 393-400.]
[4]	Feng YH, Huang JF, Chen CC, Pan XS, He TB, Pan J, Fan LL, Ji HT (2012). Preliminary approach on adaptability of ORYZA2000 model for single cropping rice in Guiyang region. Chinese Agricultural Science Bulletin, 28(9), 26-32. (in Chinese with English abstract).
	[ 冯跃华, 黄敬峰, 陈长青, 潘兴书, 何腾兵, 潘剑, 范乐乐, 纪洪亭 (2012). 基于ORYZA2000模型模拟贵阳地区一季中稻的适应性初探. 中国农学通报, 28(9), 26-32.]
[5]	Julia C, Dingkuhn M (2013). Predicting temperature induced sterility of rice spikelets requires simulation of crop-generated microclimate. European Journal of Agronomy, 49, 50-60. DOI URL
[6]	Larijani BA, Sarvestani ZT, Nematzadeh G, Manschadi AM, Amiri E (2011). Simulating phenology, growth and yield of transplanted rice at different seedling ages in northern Iran using ORYZA2000. Rice Science, 18, 321-334.
[7]	Li YL, Cui YL, Li YH (2005). Validation and evaluation of ORYZA2000 under water and nitrogen limited conditions. Journal of Irrigation and Drainage, 24(1), 28-32, 44. (in Chinese with English abstract).
	[ 李亚龙, 崔远来, 李远华 (2005). 水-氮联合限制条件下对水稻生产模型ORYZA2000的验证与评价. 灌溉排水学报, 24(1), 28-32, 44.]
[8]	Mo ZH, Feng LP, Zou HP, Wang J, Huang WH, Yang XG (2011). Validation and adaptability evaluation of rice growth model ORYZA2000 in double cropping rice area of Hunan Province. Acta Ecologica Sinica, 31, 4628-4637. (in Chinese with English abstract).
	[ 莫志鸿, 冯利平, 邹海平, 王靖, 黄晚华, 杨晓光 (2011). 水稻模型ORYZA2000在湖南双季稻区的验证与适应性评价. 生态学报, 31, 4628-4637.]
[9]	Shuai XQ, Wang SL, Ma YP, Li YC (2008). Assessment of meteorologic condition effects and dynamic yield forecasting based on rice growth model. Journal of Applied Meteorological Science, 19, 71-81. (in Chinese with English abstract).
	[ 帅细强, 王石立, 马玉平, 李迎春 (2008). 基于水稻生长模型的气象影响评价和产量动态预测. 应用气象学报, 19, 71-81.]
[10]	Soundharajan B, Sudheer KP (2013). Sensitivity analysis and auto-calibration of ORYZA2000 using simulation- optimization framework. Paddy and Water Environment, 11, 59-71.
[11]	Wang W, Cai YX, Yang JC, Zhu QS (2011). Effects of soil water deficit on physiological causes of rice grain-filling. Chinese Journal of Plant Ecology, 35, 195-202. (in Chinese with English abstract).
	[ 王维, 蔡一霞, 杨建昌, 朱庆森 (2011). 结实期土壤水分亏缺影响水稻籽粒灌浆的生理原因. 植物生态学报, 35, 195-202.]
[12]	Xie XJ, Li BB, Li YX, Li HY, Zhao XY, Yang CB, Wang ZM (2010). Effects of high temperature stress on yield components and grain quality during heading stage. Chinese Journal of Agrometeorology, 31, 411-415. (in Chinese with English abstract).
	[ 谢晓金, 李秉柏, 李映雪, 李昊宇, 赵小艳, 杨沈斌, 王志明 (2010). 抽穗期高温胁迫对水稻产量构成要素和品质的影响. 中国农业气象, 31, 411-415.]
[13]	Xie XJ, Shen SH, Li BB, Liu CL, Zhou Q (2009). Influences of high temperature stress on blooming and seed setting of rice during heading stage. Chinese Journal of Agrometeorology, 30, 252-256. (in Chinese with English abstract).
	[ 谢晓金, 申双和, 李秉柏, 刘春雷, 周千 (2009). 抽穗期高温胁迫对水稻开花结实的影响. 中国农业气象, 30, 252-256.]
[14]	Xue CY, Yang XG, Chen HL, Feng LP, Wang HQ (2010). Determining suitable sowing dates for aerobic rice in Beijing area using the ORYZA2000 model. Acta Ecologica Sinica, 30, 6970-6979. (in Chinese with English abstract).
	[ 薛昌颖, 杨晓光, 陈怀亮, 冯利平, 王化琪 (2010). 基于ORYZA2000模型的北京地区旱稻适宜播种期分析. 生态学报, 30, 6970-6979.]
[15]	Yadav S, Li T, Humphreys E, Gill G, Kukal SS (2011). Evaluation and application of ORYZA2000 for irrigation scheduling of puddled transplanted rice in north west India. Field Crops Research, 122, 104-117.
[16]	Yao FM, Xu YL, Feng Q, Lin ED, Yan XD (2005). Simulation and validation of CERES-Rice model in main rice ecological zones in China. Acta Agronomica Sinica, 31, 545-550. (in Chinese with English abstract).
	[ 姚凤梅, 许吟隆, 冯强, 林而达, 延晓冬 (2005). CERES-Rice模型在中国主要水稻生态区的模拟及其检验. 作物学报, 31, 545-550.]
[17]	Yang CB (2008). Study on Rice Mapping and Rice Yield Estimation Based on ASAR Data. PhD dissertation, Nanjing University of Information Science and Technology, Nanjing. 69-87. (in Chinese with English abstract)
	[ 杨沈斌 (2008). 基于ASAR数据的水稻制图与水稻估产研究. 博士学位论文, 南京信息工程大学, 南京, 69-87.]
[18]	Yu K, Song J, Gao P (2008). Characteristics of heat damage for rice in Jiangsu province. Scientia Meteorologica Sinica, 30, 530-533. (in Chinese with English abstract).
	[ 于堃, 宋静, 高苹 (2008). 江苏水稻高温热害的发生规律与特征. 气象科学, 30, 530-533]
[19]	Zhang J, Xu SH, Liu JL, Zhang JB, Fan XH (2007). Simulation of yield and nitrogen uptake of rice using ORYZA2000 model. Soils, 39, 428-432. (in Chinese with English abstract).
	[ 张俊, 徐绍辉, 刘建立, 张佳宝, 范晓晖(2007). 应用ORYZA2000模型模拟水稻产量及吸氮量. 土壤, 39, 428-432.]
[20]	Zheng JC, Zhang B, Chen LG, Du Q, Qin YS, Song J, Zhang WJ (2005). Genotypic differences in effects of high air temperature in field on rice yield components and grain quality during heading stage. Jiangsu Journal of Agricultural Sciences, 21, 249-254. (in Chinese with English abstract).
	[ 郑建初, 张彬, 陈留根, 杜群, 秦永生, 宋健, 张卫建 (2005). 抽穗期高温对水稻产量构成要素和稻米品质的影响及其基因型差异. 江苏农业学报, 21, 249-254.]